tag:blogger.com,1999:blog-338105413591367842024-03-12T21:24:18.317-07:00Collective BehaviorDavid Sumpterhttp://www.blogger.com/profile/09916867606281043665noreply@blogger.comBlogger37125tag:blogger.com,1999:blog-33810541359136784.post-65043017714065313822014-09-15T09:20:00.000-07:002014-09-18T02:31:35.822-07:00Open Science 4.0<div class="separator" style="clear: both; text-align: center;">
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<strong>From today our research group will change the way we communicate science.
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In recent years, we have always published open access and communicate what we do in the media. But during this coming academic year we will start a new, much more open way of communicating what we do.<br />
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Instead of basing our research solely around a series of academic papers, we will use the new <a href="http://www.collective-behavior.com/">collective-behavior website</a> to communicate our results before, during and after they are published. We will also communicate smaller, interesting results that may never make it in to published papers but are central to debates in science and society. We will do interactive science, where we take in suggestions about what we should work on and provide rapid results.
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<a href="http://www.collective-behavior.com/wp-content/uploads/2014/09/photo1.jpg" style="clear: right; float: right; margin-bottom: 1em; margin-left: 1em;"><img alt="photo" class="aligncenter wp-image-345 size-large" src="http://www.collective-behavior.com/wp-content/uploads/2014/09/photo1-1024x437.jpg" height="200" width="470" /></a>The overall aim is to do research that is useful and relevant. We want to allow our academic colleagues and members of the public to interact with us and assess and provide input on our work. With today’s technology it is easy to communicate and the direct feedback from this can improve the quality of the research we do. Our research group is made up of public servants, employed either by the state or by charitable foundations. And we therefore have a responsibility to provide results that are interesting for society. There is no excuse for not making a proper effort to tell the people who pay our salaries what we are doing with their money.
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The challenge will be to improve speed and accessibility of communication without reducing quality. Our answer is to write 500-1500 word analysis pieces where we use our skills as mathematical modellers and scientists to answer specific questions. Our aim is to reach much more widely than our current research circle. For example, one of the first articles on the new webpage is an analysis of <a href="http://www.collective-behavior.com/?p=172">pop charts using a gravity model</a>. This is a fun application of our research, illustrating how the methods we use can shed light on the every day phenomena of popularity. Another example that will appear soon is a Turing Test for fish schools: can you tell the difference between a simulated fish school and a real one? As well as the fun-side of research we will deal with important issues in society. For example, in an upcoming piece, we extend on empirical work on segregation in biology departments, using a model to understand what we can do to improve equality in universities.<br />
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Other web articles will directly extend our published work, <a href="http://www.collective-behavior.com/?p=153">such as a post today on how countries across the world have become more emancipated</a>. We will of course continue to publish regular updates on what we are up to in our usual research.
The articles we write will use the same scientific standards as we use in all our research, but with less literature background and more concise, clear language. We will communicate ideas, rapidly and clearly, so as to be useful both to other researchers and the general public. We aim to write to a high scientific standard and refer to peer reviewed articles. That said, we encourage you as a reader to put our work in a wider context, both through following the links we give and by consulting other parts of the literature.
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The change starts now, and over the next few weeks more articles will start appearing on our <a href="http://www.collective-behavior.com/">www.collective-behavior.com</a>. So welcome to our own version of Open Science 4.0!
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<i> This is a copy post and can also be read on the site itself.</i>David Sumpterhttp://www.blogger.com/profile/09916867606281043665noreply@blogger.com0tag:blogger.com,1999:blog-33810541359136784.post-81466316117064209212014-08-28T04:37:00.002-07:002014-08-28T04:37:22.153-07:00"Well duh!" When sheepdog 'robots' failI always like having a bit of media coverage of what I do. Part of it is the purely narcissistic enjoyment of lots of other people simultaneously taking an interest in our work. But there is also a genuine insight to be had from reading what the wider world thinks about research.<br />
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<table cellpadding="0" cellspacing="0" class="tr-caption-container" style="float: right; margin-left: 1em; text-align: right;"><tbody>
<tr><td style="text-align: center;"><a href="http://4.bp.blogspot.com/-kNMGrXl1K0E/U_8TKI-vhBI/AAAAAAAAAPQ/9DZU5VqB4Ao/s1600/SheepDrive.jpg" imageanchor="1" style="clear: right; margin-bottom: 1em; margin-left: auto; margin-right: auto;"><img border="0" src="http://4.bp.blogspot.com/-kNMGrXl1K0E/U_8TKI-vhBI/AAAAAAAAAPQ/9DZU5VqB4Ao/s1600/SheepDrive.jpg" height="253" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Tracks of a simulated sheep dog (blue line) 'driving' <br />and 'collecting' sheep (black lines/ red dots)</td></tr>
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Yesterday, Daniel Strömbom and Andrew King, together with myself and several other co-authors, published our paper on sheepdog and sheep interactions. The paper proposes a model for how a dog rounds up sheep. The basic idea behind the model is that in order to drive the sheep forward, the dog gets behind the flock and moves towards it. Then, if the herd becomes too wide it goes to a point which drives the furthest out sheep back towards the group. The result is a zigzagging motion as the <br />
dog takes the sheep towards the pen.<br />
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The elegance, I think, of the result lies in the simplicity of the algorithm. Previous work had proposed more elaborate rounding up schemes, which were not as good at collecting large numbers of flocking individuals. And Daniel's algorithm also nicely matches the data which Andy had collected. The dogs use the same simple algorithm as we show works so well in computer simulations.<br />
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The media were also pretty interested in our results. <a href="http://www.bbc.co.uk/iplayer/episode/b04fcl1w/bbc-news-at-one-27082014">Andy was on BBC radio</a>, Daniel and Andy were quoted repeatedly in <a href="http://www.independent.co.uk/life-style/gadgets-and-tech/news/robot-sheepdog-technology-could-be-used-to-save-people-from-burning-buildings-9692100.html">different newspapers</a> and Jose Halloy stepped in did an interview for French radio. The reports were enthusiastic, talking about the possible development of autonomous robots inspired by our research. But looking at the comment sections of some of the newspaper articles, not all readers were completely convinced. One of the main points can be summarised by the following quote on the Guardian's website<br />
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"<span style="background-color: white; color: #333333; font-family: Helvetica, Arial, sans-serif; font-size: 13px; line-height: 15px;">This is one of those "Well duh!" is discoveries, isn't it? </span><span style="background-color: white; color: #333333; font-family: Helvetica, Arial, sans-serif; font-size: 13px; line-height: 15px;">I just don't know how farmers have managed for centuries without this research." </span><br />
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Why the hell are scientists wasting time telling us something we have known for years?<br />
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The answer to this critique lies in the details. It is one thing to know that dogs go back and forward behind sheep, another to show that a simple 'collect' and 'drive' mechanism works properly. This is what is done in the paper, by showing when the algorithm works and when it doesn't. And it is when it fails that the insight are might be greatest. One thing not covered by the media is that when trying to round up very big groups of sheep our 'robot' sheepdog sometimes got confused. This is shown in the video below. The simulated dog gets caught between two groups and can't continue.<br />
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So we don't fully understand how sheepdogs solve large scale herding problems, and we still don't know how and to what extent real dogs can solve these problems. I can think of some plausible answers, such as dogs giving up and repositioning themselves after a time, but testing these requires more work and more experiments. In fact, there are lots of things neither scientists nor anyone else understands about flocking and herding in general, and there is certainly nothing obvious about the answers.<br />
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<br />David Sumpterhttp://www.blogger.com/profile/09916867606281043665noreply@blogger.com0tag:blogger.com,1999:blog-33810541359136784.post-74500204896036914632014-08-16T23:47:00.001-07:002014-08-17T22:33:52.333-07:00Hamilton's rule as a tautology.Wilson and Nowak have published a new '<a href="http://www.pnas.org/content/early/2014/08/06/1405550111.full.pdf">perspective</a>' on the evolution of sociality in ants. It combines "palaeontology, phylogeny, and the study of contemporary life histories" to try to give more insight in to this question. This is their latest addition to a <a href="http://www.nature.com/nature/journal/v471/n7339/full/nature09831.html">long running debate</a>, between these two <a href="http://ftp.eebweb.arizona.edu/faculty/dornhaus/courses/read_ECOL597S/Nowak%20Tarnita%20Wilson%20evolution%20of%20eusociality.pdf">Harvard professors</a> and (it seems) almost everyone else in evolutionary biology, on whether <a href="http://en.wikipedia.org/wiki/Kin_selection">Hamilton's rule</a> explains social evolution. After earlier attempts to provide mathematical models of the evolution of sociality in ants, bees and wasps, Wilson and Nowak seem to have returned to a more natural history based description. However, as Iain Couzin pointed out on <a href="https://twitter.com/icouzin">Twitter</a> they "argue for the need for a mathematical description, but provide no mathematical description".<br />
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<a href="http://2.bp.blogspot.com/-dJTHTb9s3Ew/U_GN-esj8xI/AAAAAAAAAO8/1eM-N2ptfEY/s1600/Taut.png" imageanchor="1" style="clear: right; float: right; margin-bottom: 1em; margin-left: 1em;"><img border="0" src="http://2.bp.blogspot.com/-dJTHTb9s3Ew/U_GN-esj8xI/AAAAAAAAAO8/1eM-N2ptfEY/s1600/Taut.png" height="180" width="320" /></a>I have a love/hate relationship with literature on the 'evolution of co-operation'. It usually involves nice mathematics and undergraduate maths students enjoy doing projects on it. But my main problem is that it does not produce empirically testable predictions. In the past, many of the <a href="http://www.researchgate.net/publication/6641993_Five_rules_for_the_evolution_of_cooperation/file/60b7d52462c9120e92.pdf">papers by Nowak</a>, his co-workers and other mathematical biologists working on the evolution of co-operation problem don't really specify what type of biological system they are trying to represent. With the exception of the current paper, Nowak's group appear to have settled on <a href="http://www.fas.harvard.edu/~ped/people/faculty/publications_nowak/RandTrendsCognSci2013.pdf">humans</a> and this is fine, but prior to this he proposed various abstract rules of co-operation that were fun, but lacked experimental prediction.<br />
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It was slightly ironic then that <a href="http://www.nature.com/nature/journal/v466/n7310/abs/nature09205.html">Nowak et al. (2010)</a> decided to so forcefully attack Hamilton's rule on failing to make empirical predictions. <a href="http://www.amazon.com/Narrow-Roads-Gene-Land-Collected/dp/0716745305">Hamilton's papers</a> are full of empirical predictions, and as the <a href="http://www.nature.com/nature/journal/v471/n7339/full/nature09831.html">100+ authors who replied to the 2010 paper</a> point out, it is helpful in settings ranging from sex allocation to parasite vigilance.<br />
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BUT, and this is a capital letters 'but', the paper by <a href="http://www.nature.com/nature/journal/v466/n7310/abs/nature09205.html">Nowak et al. (2010)</a> was not about these other settings, it was about the evolution of eusociality, as defined by Wilson himself. Explaining eusociality has to be done in terms of the social interactions of animals or other organisms. And Nowak et al. (2010) are correct in their key point. Hamilton's rule is not a general equation for evolution of mechanisms. It is the other way round. Once we have described the mechanism for gene flow and social interactions it is possible to find a Hamilton's rule that gives the condition for the evolution of co-operation. <br />
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At first sight, this might appear to make Hamilton's rule extremely powerful. Hamilton's rule shows us that properly calculating costs, benefits and relatedness between individuals tells us the course natural selection takes. Hamilton’s rule can then be thought of as a fundamental accounting rule that must hold in order for a particular behaviour to evolve. But the same thinking shows a serious weakness. Hamilton’s rule becomes a tautology, a statement of necessary truth. By summing up costs and benefits in the right way we can find a Hamilton’s rule for every biological system. Instead of producing fundamental understanding, discussing Hamilton’s rule becomes an argument like whether we should add the rows or columns first when summing all entries on an Excel spreadsheet. Different methods give the same answer, and there is no reason to call either method fundamental.<br />
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To illustrate this, Nowak et al. reformulated Hamilton's rule as<br />
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'something' b>c<br />
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where the ‘something’ was whatever came out of making the world fit in to Hamilton’s rule. I think this equation makes the point extremely well. Relatedness is of course important in evolution, but Hamilton's rule is a meaningless equation.<br />
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Together with two <a href="http://www.math.uu.se/~david/web/Lehmannetal07.pdf">Laurents (Lehmann and Keller)</a> a few years ago, we showed that one of Nowak and co-workers much touted 'new' rules for co-operation was just<br />
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relatedness > 'something c'/'something b'<br />
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where we could find the 'something c' and 'something b' from the underlying social interaction. At that point, we were stressing that there can't be <a href="http://www.researchgate.net/publication/6641993_Five_rules_for_the_evolution_of_cooperation/file/60b7d52462c9120e92.pdf">5 or whatever number of rules for co-opertation</a> that Nowak was promoting at the time. Depending on how you want to look at it, there is only one (Hamilton's rule) or infinitely many. In hindsight I would have laid more stress on the "infinitely many" part than we did then, and this is what Wilson and Nowak's new paper stresses (although I don't quite know how Nowak reconciles his current position with the 5 rules he found earlier). Hamilton's rule (used in the context of population genetics) is the ring that binds all these different explanations of co-operation together, but only because it always applies. There is no such thing as magic.<br />
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I should point out that, while the 'something' equation in the <a href="http://www.nature.com/nature/journal/v466/n7310/abs/nature09205.html">Nowak et al. (2010)</a> is interesting, the rest of the paper seems to me to be hyperbole mixed with a standard group selection model. The reply by <a href="http://www.nature.com/nature/journal/v471/n7339/full/nature09832.html">Boomsma et al.</a> highlights a serious problem with the explanation provided: relatedness is high in clades that have evolved to be social. High relatedness gives a simple and convincing explanation consistent with the reasoning Hamilton may have offered. This is good empirically grounded science. I will now have to study Wlison & Nowak's latest perspective in more detail to see if they can adress this point.<br />
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<br />David Sumpterhttp://www.blogger.com/profile/09916867606281043665noreply@blogger.com2tag:blogger.com,1999:blog-33810541359136784.post-60267037277750318972014-08-06T05:27:00.001-07:002014-08-06T23:52:13.939-07:00Super fluid starlings and other physical analogies.Last week a new article on starling flocks was published by the <a href="http://www.sapienza.isc.cnr.it/biological-systems/flocking.html">COBBS group in Rome</a>. This research group, led by physicist couple Irene Giardina and Andrea Cavagna, are a great example of the <a href="http://collective-behavior.blogspot.se/2014/05/the-motion-of-collective-motion.html">varied background of researchers working in collective behavior</a>. They started as theoretical physicists, but wondered how their skills could be applied elsewhere. Such interdisciplinary thinking by physicists isn't uncommon. Physicists often think that their models and tools will be useful for a whole range of things, from <a href="http://web.aalto.fi/en/current/news/2012-10-24/">voting and elections</a>, to the <a href="http://www.scientificamerican.com/article/sand-pile-model-of-the-mind-grows-in-popularity/">structure of the brain</a> and, of course, animal groups.<br />
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<table cellpadding="0" cellspacing="0" class="tr-caption-container" style="float: right; margin-left: 1em; text-align: right;"><tbody>
<tr><td style="text-align: center;"><a href="http://wwwp.cord.edu/faculty/ulnessd/legacy/fall06/adam/adam_files/master03_background.jpg" imageanchor="1" style="clear: right; margin-bottom: 1em; margin-left: auto; margin-right: auto;"><img border="0" src="http://wwwp.cord.edu/faculty/ulnessd/legacy/fall06/adam/adam_files/master03_background.jpg" height="239" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Droplet of super fluid helium. <br />
Taken from talk by <a href="http://wwwp.cord.edu/faculty/ulnessd/legacy/fall06/adam/adam_files/frame.htm">Adam Hokkanen</a>.</td></tr>
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The idea in the current study is that mathematical models are used to draw an analogy between <a href="http://news.sciencemag.org/math/2014/07/how-bird-flocks-are-liquid-helium">starling flocks and liquid fluid helium</a>. Waves of turning propagate through the whole group very quickly. So quickly that it can appear they change direction in unison. What the Rome physicists found out was that there is a clear ordering in the turning, with individuals successively copying the direction of their neighbours. The analogy between super fluidity and starlings can be found in a relation between alignment and speed of turning. The higher the alignment of the group, the faster turning propagates through it.<br />
physics and biology.<br />
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How are we meant to interpret analogies like this? Should we take them seriously and think that helium and starlings are just the same types of particles? Or should we see the similarity as just a loose rhetoric device? A way of getting the readers attention? These are the sorts of questions that are important if our aim is to apply mathematical models to make analogies. But the answer you get if you ask a theoretical physicists and mathematicians can vary greatly. They can also vary if you ask the same person on different days of the week.<br />
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Some physicists take these analogies very seriously indeed. I have been told on quite a few occasions that an experiment on ants or fish is unnecessary because it is "already proved by trivial symmetries in the system". Other times the analogies are made too loosely. No-one could be expected to believe that what is true for magnets is equally true for opinions about upcoming elections, yet this pretty much the assumption in many 'voter' models. The argument is sometimes made that the two systems have "deep parallels" and that the differences between iron filings and people are surface properties!<br />
Other times, the argument is made that these analogies "capture the public's imagination" and are useful for communication.<br />
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I wouldn't argue that there is more than one correct way to make an analogy. However, there is a rule which I think should be followed and it is this:<br />
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<b>Modelling analogies between a physical and biological systems should be based on empirical observations from both of the systems.</b><br />
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<table cellpadding="0" cellspacing="0" class="tr-caption-container" style="float: left; margin-right: 1em;"><tbody>
<tr><td style="text-align: center;"><a href="http://1.bp.blogspot.com/-9XDWT_Nnc0I/U-Idasl-tUI/AAAAAAAAAOo/F9xTeKoFbzY/s1600/FlowStarlings.jpg" imageanchor="1" style="clear: left; margin-bottom: 1em; margin-left: auto; margin-right: auto;"><img alt="" border="0" src="http://1.bp.blogspot.com/-9XDWT_Nnc0I/U-Idasl-tUI/AAAAAAAAAOo/F9xTeKoFbzY/s1600/FlowStarlings.jpg" height="320" title="" width="264" /></a></td></tr>
<tr><td class="tr-caption" style="font-size: 13px; text-align: center;">Flow of starlings in a murmuration. <br />
From <a href="http://www.annualreviews.org/doi/abs/10.1146/annurev-conmatphys-031113-133834">Cavagna & Giardina (2014)</a></td></tr>
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This is where Andrea, Irene and the Rome team have excelled. Their starling and midge data has set new standards in 3D reconstruction of movement of animal groups. They aren't satisfied with just speculating on similarities, but check the details. And they have made big steps in <a href="http://arxiv.org/pdf/0802.1668.pdf">collective animal behaviour</a> along the way. They are very clear about the importance of <a href="http://www.annualreviews.org/doi/pdf/10.1146/annurev-conmatphys-031113-133834">statistical mechanics tools in the way they work</a>, and use analogies like the superfluity and phase transitions, but always couple back to the biology.<br />
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This is when physical analogies are at there best. When we use mathematical tools, careful experiment and lateral thinking all mixed together.David Sumpterhttp://www.blogger.com/profile/09916867606281043665noreply@blogger.com0tag:blogger.com,1999:blog-33810541359136784.post-10440264118974292282014-07-29T01:17:00.002-07:002014-07-29T01:17:12.544-07:00Waves of insect sound<div class="separator" style="clear: both; text-align: center;">
<a href="http://2.bp.blogspot.com/-K-7XxIW_dEo/U9dLxzqRR1I/AAAAAAAAAOY/Hj3yG179Rzs/s1600/CicadaEvening.png" imageanchor="1" style="clear: right; float: right; margin-bottom: 1em; margin-left: 1em;"><img border="0" src="http://2.bp.blogspot.com/-K-7XxIW_dEo/U9dLxzqRR1I/AAAAAAAAAOY/Hj3yG179Rzs/s1600/CicadaEvening.png" height="234" width="320" /></a></div>
On Friday, James "Teddy" Herbert-Read will present our recent work on synchronized cicada calling at <a href="http://www.isbe2014.com/">ISBE2014</a>. This project started when Teddy's parents invited my family to stay at their house in Port Macquarie, about 4 hours drive north of Sydney. Teddy's parents are brilliant hosts, and each evening Lovisa (my wife), Teddy and myself would find ourselves sitting on their verandah, gin and tonic in hand, looking out on a beautiful sunset. Kangaroos hopped around on the lawn in front of the house.<br />
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Then the cicadas starting singing. At first they produced a low background hum, but as the evening went on the volume increased. It didn't increase steadily, but in waves. At first it was low, then it got louder and finally we could hardly hear ourselves speak. Suddenly it stopped again, and for a while the peace and tranquility was restored. But after about ten seconds or so it started up again. And on it went, loud chirping, followed by a pause and chirping again.<br />
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Lovisa, Teddy and I set off, gin and tonic in one hand iPhone in the other, to the edge of the bush and set up recording stations 100m apart. We left our phones in the forest and returned to enjoy dinner on the terrace. After dinner and night fall, we returned to look for our phones. After a bit of stumbling about with torches, and one close Kangaroo encounter for Teddy and my son Henry, we recovered them. We downloaded and looked at the sound files. The pattern was immediate and striking. First Lovisa's phone, from the top of the hill, had a peak in volume. A few seconds later, my phone from the middle of the hill peaked, and lastly Teddy's from the bottom of the hill peaked. It looked like a wave of sound was traveling down the hill.<br />
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Even for a mathematician like me, microphones placed out after a few evening drinks do not constitute an experiment. Luckily, Teddy volunteered to return to his parents and do the hard work, this time completely sober. He placed out microphones and measuring the waves of cicada sounds over different areas near his parents house. If you are in New York on Friday you can find out more. If not the video below gives a little taster. The size of the circles give the volume at different positions round the forest. Watch how the noise spreads from top to bottom.<br />
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Much of our analysis of this data will be inspired by earlier work on synchronized <a href="http://www.scientificamerican.com/article/how-and-why-do-fireflies/">firefly flashing</a> and the models by <a href="http://www.stevenstrogatz.com/">Steve Strogatz</a> and others on coupled oscillators. You can also read more about these types of synchronization in <a href="http://www.collective-behavior.com/publ/SumpterChapter7.pdf">chapter 6 of my book on Collective Animal Behavior</a>. Teddy's talk is on <a href="http://www.isbe2014.com/uploads/1/7/4/5/17452123/index_current.xlsx">Friday at 3:20</a>.David Sumpterhttp://www.blogger.com/profile/09916867606281043665noreply@blogger.com0tag:blogger.com,1999:blog-33810541359136784.post-84904136170142502752014-07-25T06:21:00.000-07:002014-07-25T06:23:21.546-07:00In memory of Dave Broomhead<a href="http://2.bp.blogspot.com/-vRvvzkvxtoI/U9JYPgt0sOI/AAAAAAAAAOI/7x05fa3svXI/s1600/Dave.jpg" imageanchor="1" style="clear: right; float: right; margin-bottom: 1em; margin-left: 1em;"><img border="0" src="http://2.bp.blogspot.com/-vRvvzkvxtoI/U9JYPgt0sOI/AAAAAAAAAOI/7x05fa3svXI/s1600/Dave.jpg" height="269" width="320" /></a>I found out yesterday that my PhD supervisor Dave Broomhead has died.<br />
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Dave was an amazing person and academic. For me, the thing that summed up Dave was his enormous faith in the goodness and ability of other people. His belief that everyone was doing their best may seem foreign to the competitive world of academia, where so many of us think our own work is the most important. But Dave's faith in others meant, not only that he was universally liked and respected by everyone he met, but that he could do research in a clear, methodological and honest way. I have many examples of his approach to life and academia, but those I give below are the ones that are most special to me.<br />
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When I started my PhD, I couldn't write. I had studied science and computing at school and University and never really got the hang of grammar or style. Dave took one look at the first draft of a paper I wrote and said "This isn't an article, its written like a computer program!". My feeling was that I was doing a PhD in maths, and writing was for journalists. Dave saw it differently. He set in place a Tuesday evening routine. We would go out and eat dinner together. He always paid. Then we would go back to his office. I would sit at his computer and he would lie flat on the floor behind me. He would ask me to read, line after line of the stuff I had written and make suggestions and corrections, not letting me move on until he was happy. The first two paragraphs of the 'Introduction' took about a month to write. I just reread <a href="http://www2.math.uu.se/~david/web/SumpterBroomhead00.pdf">these paragraphs</a> now and see that they sum up much of my research over the next 10 years. Through these evening sessions, Dave taught me not only to write, but to organize my thoughts and solve problems.<br />
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It wasn't just his PhD students, to whom Dave gave time and space. He always listened carefully to anyone who talked to him: family, friend, academic, cleaner, or random person in the pub. I once asked him to chair a session at a meeting at the Newton Institute in Cambridge. In many ways, Dave was the worst possible moderator. He never interrupted the speaker, even when they were 10 or 15 minutes over time. By the end of the session we were running 40 minutes late. Dave had asked if there were any last questions for the final speaker. He looked around. No takers. Finally, after a long pause he said the speaker"…..OK, could you put up your 5th slide again….as you said I think there could be an interesting consequence if you took in to account…." and so it went on. When I asked about it afterwards he lightly reprimanded me for my impatience: "if people have come all this way to give a talk then we have to let them tell us everything that is on their mind, otherwise we'll never understand anything."<br />
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This faith in others pervaded his thinking about how academia should be run. He was opposed to all the forms of evaluations, rankings and assessment exercises that went on during his time in Manchester. His basic assumption was that anyone working in academia was doing it because they loved it as much as he did. If his colleagues failed to publish anything, it was because they hadn't yet found something worth telling other people about. Why publish a paper unless you really has something worthwhile to say? Better to wait until you had really solved the problem, and no point harassing those who hadn't got there yet.<br />
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His own research was grounded in a patient respect for what others had done combined with an extremely deep thinking of his own. He invented a <a href="http://scholar.google.se/citations?view_op=view_citation&hl=en&user=xK5Dgc4AAAAJ&citation_for_view=xK5Dgc4AAAAJ:WA5NYHcadZ8C">whole new field of radial basis neural networks</a>, because he was carefully going through and "spotted a simplification which the authors seemed to have missed". His influential work on <a href="http://scholar.google.se/citations?view_op=view_citation&hl=en&user=xK5Dgc4AAAAJ&citation_for_view=xK5Dgc4AAAAJ:u-x6o8ySG0sC">time series analysis</a>, took an abstract part of topology, in the form of Taken's embedding theory, and solved problems in detecting and understanding chaotic signals. Last time I saw him present his research he was using <a href="http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=6518042&url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D6518042">abstract algebra to solving computer communication timing problems</a>. He used to joke that it didn't matter how 'pure' a mathematician thought their work was, he could take their work and make a useful application.<br />
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I last saw Dave three years ago, at home in Malvern with his wife Eleanor. I have seldom met two people with so much love and compassion for one another. I felt so much at home sitting in their house, talking to them both about their time as PhD students together in Oxford and their pride in their son Nathan. It is difficult for everyone when such an amazing person as Dave is lost, but his wonderful way of seeing life will never disappear.<br />
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<tr><td class="tr-caption" style="text-align: center;">Drawing by Dave, stolen by me from his Facebook page.</td></tr>
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<br />David Sumpterhttp://www.blogger.com/profile/09916867606281043665noreply@blogger.com4tag:blogger.com,1999:blog-33810541359136784.post-84248510135242371682014-07-13T11:32:00.002-07:002014-07-13T11:41:11.428-07:00The mystery of nothingness<a href="https://pbs.twimg.com/media/Bsady3PIEAAG7dm.jpg:large" imageanchor="1" style="clear: right; float: right; margin-bottom: 1em; margin-left: 1em;"><img border="0" height="223" src="https://pbs.twimg.com/media/Bsady3PIEAAG7dm.jpg:large" width="320" /></a>Yesterday evening, arriving home from a few days away, my wife found I package addressed to me. I don't get real post very often so this was quite exciting. I opened it up to find two identical gift wrapped packages. Opening them up I found two almost identical books, entitled 'Being or Nothingness'. I say almost identical, because one of the books had a wax seal and string round it, and came in a box with my name and the number 1260 on it. The other could be opened easily, and had number 0027 and name <a href="http://en.wikipedia.org/wiki/Alvar_Elleg%C3%A5rd">Alvar Ellegård</a> on it.<br />
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I opened the unsealed book this morning and read it through. It consisted of 21 pages of quotations and mysteries relating to Sherlock Holmes, <a href="http://www.soic.indiana.edu/people/profiles/hofstadter-douglas.shtml">Douglas Hofstadter</a>, Satre, Hermann Hesse, Kafka. the Bible, various philosophers, Hitchhikers Guide to the Galaxy and other literature. It claimed to be a riddle that could only be solved through careful study. I couldn't really see the answer, but it was written down the lines of Hofstedter's other work (he wrote Gödel, Esher and Bach), and I concluded that it could be some kind of part of his work. I heard Hofstedter talk in Uppsala a few years ago about the <a href="https://www.youtube.com/watch?v=n8m7lFQ3njk">importance of analogy</a>, and thought he could be trying to experiment down those lines.<br />
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<iframe allowfullscreen='allowfullscreen' webkitallowfullscreen='webkitallowfullscreen' mozallowfullscreen='mozallowfullscreen' width='320' height='266' src='https://www.youtube.com/embed/RL18Q1C9SKI?feature=player_embedded' frameborder='0'></iframe>I thought it might be a birthday present and I should solve it myself, so I didn't look it up on the Internet. But when I got nowhere my wife Lovisa looked it up. Apparently this is the second time it has come out. The first was in 2008 and there were various theories, from viral marketing, Christians trying to convince scientists of the error of their ways to it being the work of a mad psychiatrist from Gothenburg (where the package was sent from). Lovisa thinks its an art project. Jon Ronson apparently wrote about the mystery in a book on <a href="http://www.amazon.com/The-Psychopath-Test-Journey-Industry/dp/1594485755">psychopaths</a>. There is also a strange video about a student's encounter with Hofstadter that relates to the book. But no real answers. It appears that in the latest release it has been sent to Swedish media people and academics, and they have now made a <a href="https://www.facebook.com/groups/627073014056486/">Facebook group</a> (in Swedish) to document what is known.<br />
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What is remarkable about the whole thing is the quality of the book. I get emails every day telling me that the sender has shown that pi is a rational number or solved the mystery of quantum physics or something. But his book is of extremely high quality print, with a very professional feel that gives no clear indication of what it is trying to achieve. You can see it online <a href="http://levishand.wordpress.com/2009/05/04/the-book/">here</a>, but this doesn't capture the way the whole package was constructed. It also gives the aura of a genuine mystery, with clues going in different directions. The small number of details on the internet also seem to lead in very diverse directions. I don't know the answer to the mystery, but it was certainly a fun thing to get in the post.<br />
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<br />David Sumpterhttp://www.blogger.com/profile/09916867606281043665noreply@blogger.com0tag:blogger.com,1999:blog-33810541359136784.post-87055263109339736772014-06-30T11:58:00.001-07:002014-06-30T11:58:59.081-07:00Despite emotions, Facebook is not contagiousI am not one of those researchers who are "<a href="http://www.fastcompany.com/3032523/most-innovative-companies-2014/why-academics-are-incensed-by-facebooks-emotion-manipulating-?utm_source=facebook">outraged</a>" by Facebook's emotional manipulation study. Facebook, Google and Twitter make their living by manipulating our emotions. These companies continually manipulate what we see when we go online, usually so we keep coming back for more. In this context, it doesn't seem so terrible that they sometimes use their power to make new interesting scientific findings.<br />
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<tr><td class="tr-caption" style="text-align: center;"><a href="http://www.pnas.org/content/111/24/8788.figures-only">Figure from Kramer et al. showing effects <br />measured in 'social contagion' study.</a></td></tr>
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I am however doubtful about aspects of the result presented in the new <a href="http://www.pnas.org/content/111/24/8788.full">PNAS article</a>. The authors claim to provide "experimental evidence for massive-scale contagion via social networks" and "first experimental evidence to support the controversial claims that emotions can spread throughout a network". What is actually provided is a rather weak effect. In the experiment, the authors removed between 10% and 90% of positive posts from people's news feed and found that the percentage of positive words used dropped from around 5.25% to just over 5.1%. I show the results figure from the paper on the right so you can see the results yourself.<br />
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So what does this result mean in terms of social contagion? Imagine I have 100 friends on Facebook and 50 of them stop writing positive things online. If I write 100 words a day on Facebook, then according to the experimental results, during one week I will write a total of one less positive word. Maybe on Wednesday I'll write 'OK' instead of 'Good'. This lost 'good' will have almost no effect on my friends. Of the 70000 words they might read in a week (assuming everyone is like me and writes 100 words a day and has 100 friends) one of them will be less positive. There is no way that this type of effect will turn in to a "contagion". My potential 'good' will be lost in a noise of 'likes' and smiley faces. Quite quickly everyone will recover from negative thinking and the balance of happy and sad words will return to normal levels.<br />
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The authors partially acknowledge my point saying that "the effect sizes from the manipulations are small" but claim that "the massive scale of social networks such as Facebook, even small effects can have large aggregated consequences". While this statement is true, my argument above shows that the aggregation works against contagion, not in favor of it. I could make this argument more thorough, accounting for interactions between individuals and calculating <a href="http://en.wikipedia.org/wiki/Basic_reproduction_number">R0</a>, but the result will be the same. The Kramer et al. study show that emotions are negligibly contagious on Facebook.<br />
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Overall, the Facebook study is a useful contribution to the literature and I am glad to see it published. What concerns me is how quickly an idea like 'online emotions are contagious' can spread without anyone checking the basics. Scientific ideas <b>are</b> contagious and often spread unchecked (although maybe I should check how strong this effect actually is before I make such claims :-) ).David Sumpterhttp://www.blogger.com/profile/09916867606281043665noreply@blogger.com0tag:blogger.com,1999:blog-33810541359136784.post-88409467415008825202014-06-26T01:17:00.000-07:002014-06-26T01:17:19.665-07:00The Collective Machine<table cellpadding="0" cellspacing="0" class="tr-caption-container" style="float: right; margin-left: 1em; text-align: right;"><tbody>
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<tr><td class="tr-caption" style="text-align: center;">Ants solve the Towers of Hanoi maze. <br />Image and experiments by <a href="https://sites.google.com/site/chrisreidbiologist/">Chris Reid</a>. </td></tr>
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Often when 'collective behavior' researchers write grant proposals we highlight the possibility of our research inspiring future computing. The idea is that if we can better understand how ants, amoeba and fish solve problems in groups we can inspire new computer design. Everyone, from the grant writers, the reviewers, and the funding bodies take these claims with a small pinch of salt. Yes, one day we might build swarm computers, but it is a bit difficult to see how <a href="file:///Users/david/Desktop/Dropbox%20(UUMD)/collective-behavior%20web/publ/Reid2011.pdf">ants solving mazes</a> really provides insights that are useful today.<br />
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A few years ago I led a research project on "Optimization in natural systems: ants, bees and slime moulds", funded by the <a href="http://www.hfsp.org/">Human Frontiers Science Programme</a>. The team consisted of myself, social insect biologist <a href="http://sydney.edu.au/science/people/madeleine.beekman.php">Madeleine Beekman</a>, slime mould expert <a href="http://news.bbc.co.uk/2/hi/science/nature/8473316.stm">Toshi Nakagaki</a>, and computer scientist <a href="http://pacosy.informatik.uni-leipzig.de/15-1-Prof+Dr+Martin+Middendorf.html">Martin Middendorf</a>. Our research was <a href="http://www.hfsp.org/frontier-science/hfsp-success-stories/making-decisions-through-collective-behaviour">very successful</a> and we learned lots about the organisms involved. But, if I am honest, we never got close to translating our results in to real progress in computing.<br />
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Or so I thought…… A couple of weeks ago I read about Hewlet Packard's new computer, called <a href="http://www.businessweek.com/articles/2014-06-19/is-hewlett-packards-the-machine-the-computer-of-the-future">The Machine</a>. According to the HP press release the machine will vastly increase the speed of computing. From the news articles alone, it is difficult to work out exactly what revolution is contained within The Machine, but the word that comes up repeatedly is <i>memristor</i>. It is here that there is a link to collective behavior in biology.<br />
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The memristor is an electronic component which changes its resistance as an electric current passes through it. This change in resistance gives the memristor its memory. It also provides an exact analogy to slime moulds and pheromone-laying ants. Slime moulds connect food sources with tubes that increase in size with flow of nutrients and ants build trails which become more attractive as the flow on them increases. In a recent paper we showed exactly how the analogy between electrical networks, slime moulds and ants <a href="http://rsif.royalsocietypublishing.org/content/10/80/20120864.full.html#ref-list-1">are explained through current re-enforced random walks</a> (the video on the right shows this algorithm solving a non-linear transport optimisation problem). Slime moulds, ants and The Machine compute in the same way.<br />
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The way these systems compute is fundamentally different from traditional computers. In a traditional computer the processor fetches from memory, performs an action, and updates memory. In memristor-based systems, memory and processing update simultaneously. This allows for massive parallel computation. One of the researchers working on our project in Uppsala, Anders Johansson, has proved that these systems can solve linear programming problems in a completely decentralized way. A small adjustment to the method can give fast approximate solutions to NP-hard problems. Anders has put some of his results <a href="http://arxiv.org/abs/1101.5249">written together with Toshi's group on the ArXiv</a> and published <a href="http://www.people.fas.harvard.edu/~jzou/pub/Slime_mold.pdf">a paper with James Zhou </a>on the linear programming proof. But I haven't managed to get him to write up a whole load of other nice results he has on these systems. Maybe 'The Machine' will inspire him to get going.<br />
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In general, despite the skepticism I started this article with, I would encourage more researchers to think in terms of distributed electrical circuits and their links to biology. It is very likely that the human brain has aspects of this type of processing in its design. And whatever The Machine might be able to do, it still can't come close to our own brains.<br />
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<br />David Sumpterhttp://www.blogger.com/profile/09916867606281043665noreply@blogger.com0tag:blogger.com,1999:blog-33810541359136784.post-28889183608829096812014-06-25T00:31:00.000-07:002014-06-25T07:41:21.700-07:00New styles of moshingIn my recent <a href="http://collective-behavior.blogspot.se/2014/04/what-is-complex-system.html">Modeling Complex Systems course</a>, the final project involved implementing a model from an article from the exisiting literature. Most of the models the students could choose from were complex systems 'classics'. For example, <a href="http://www.ped.fas.harvard.edu/people/faculty/publications_nowak/Nature92.pdf">Nowak & May's spatial games</a>; <a href="http://www.nature.com/nature/journal/v406/n6794/full/406378a0.html">Albert, Jeong & Barabasi networks</a>; <a href="http://www.nature.com/nature/journal/v433/n7025/full/nature03236.html">Couzin et al. leadership of flocks</a> were all included. But for fun I added one of my favourite papers of last year, <a href="https://cohengroup.lassp.cornell.edu/research.php?project=10017">by Silverberg et al., on mosh pits</a>.<br />
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<a href="http://i.imgur.com/xrWyStZ.png" imageanchor="1" style="clear: right; float: right; margin-bottom: 1em; margin-left: 1em;"><img border="0" src="http://i.imgur.com/xrWyStZ.png" height="212" width="320" /></a>Silverberg and colleagues first analyzed online videos to identify how rock fans behaved when moshing. An example of a 'circle pit' is shown to the left. To explain how these pits are formed, the researchers built a model which assumed two types of concertgoers, those that want to bounce around and those that want to stand still. The active, bouncing moshers were subject to three types of forces. The first force was a tendency to follow in the same direction as those around them, the second was a tendency to mosh around at random and the third was the inevitable force caused by bumping in to others. The passive moshers were subject only to the last force. When active moshers bumped in to passive bystanders they bounced off them. This model was able to reproduce both the circle pit shown in the picture and the traditional random mosh pit.<br />
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Two groups of students in my class worked through a complete re-implementation of the model. Both groups were able to reproduce the original results, but they also found that getting a mosh pit going involved quite specific initial conditions. Only if the moshers started in a pit would the pit remain stable. To address this issue they modified the model a bit. Kristoffer Jonsson and Jonas Mirza added a force that repulsed the passive concertgoers from the centre. The idea here is that the passive individuals want to avoid the centre of the pit. The active moshers then formed a stable mosh circle. This is shown in the video below.<br />
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Another group of students, John Svensson and Andreas Gådin, solved the issue by confining the moshers to a fixed area. This is a pretty realistic assumption. Heavy metal concerts do not take place on an infinite donut as is commonly assumed in this type of simulation. The change led to some new and interesting mosh patterns. The video below shows how these build up, culminating in a collective rush backwards and forwards (see around 2:30 in the video). This is reminiscent of the <a href="http://www.urbandictionary.com/define.php?term=wall%20of%20death">Wall of Death</a>, where the crowd run at each other like crazy. The striking thing here is that these walls can move backwards and forwards without the band initiating them.<br />
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Another pattern to look out for next time you are at a rock concert is the double vortex pit. This is pictured on the right and arises for specific parameter value combinations. The moshers move outwards in two ways, crash in the middle and then move out again.<br />
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The striking aspect of all these patterns is the lack of intelligence needed to produce them. Moshers can be as stupid as they like and they will still make pretty patterns! Thinking more broadly, the rules of the model are not unlike those which might govern cells during developmental processes. These models show how simple movements, combined with the right boundary conditions, can produce many different and robust patterns.<br />
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Thank you to John, Andreas, Kristoffer and Jonas for working so hard on your projects. It makes teaching more fun when I also learn something new.<br />
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<!--StartFragment--><!--EndFragment-->David Sumpterhttp://www.blogger.com/profile/09916867606281043665noreply@blogger.com0tag:blogger.com,1999:blog-33810541359136784.post-26676645000182783952014-06-13T06:08:00.002-07:002014-06-13T06:12:31.522-07:00Flying insect swarmsI am currently writing a 'Quick Guide' for <a href="http://www.cell.com/current-biology/home">Current Biology</a> on moving insect swarms. I was inspired to write this by the recent work by the Rome group on <a href="http://www.sapienza.isc.cnr.it/component/content/article/86-research/245-cobbs-non-biting-midges.html">midge and mosquito swarms</a>. Their paper on collective motion of these Swarms is already available on <a href="http://arxiv.org/pdf/1307.5631.pdf">arxiv</a>, and will soon appear in a 'real' journal. This work was very nicely presented by Stefania Melillo and Lorenzo del Castello at the recent <a href="http://www.collectivemotion2014.net/program">Collective Motion 2014</a> meeting. My quick guide will focus on this work, and on some recent work by <a href="http://cdcl.umd.edu/">Derek Paley</a>'s group on mosquitos. And it will also take in honey bee swarms and locusts.<br />
<br />
<div class="separator" style="clear: both; text-align: center;">
<a href="https://pbs.twimg.com/media/BpTUHBmCMAMcZSm.jpg:large" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"><img border="0" height="194" src="https://pbs.twimg.com/media/BpTUHBmCMAMcZSm.jpg:large" width="320" /></a></div>
Flying insect swarms come in all shapes and sizes. Last week the USA national weather service found that a <a href="http://modernfarmer.com/2014/06/radar-picks-massive-grasshopper-swarm-albuquerque/">grasshopper swarm showed up on their weather radar</a>. The images (on the right) show the sheer scale of the swarm, which was probably flying at 700 meters. This is still relatively small compared to locust swarms, which have been reported to have flown across the Atlantic.<br />
<br />
<a href="http://4.bp.blogspot.com/-Tq-pvBZdbnA/U4ZOoXcpOaI/AAAAAAAABiw/Hl4dXGmUE-Q/s320/Filipa_Scarpa_Documental-April_Portugal_2014.jpg" imageanchor="1" style="clear: right; float: right; margin-bottom: 1em; margin-left: 1em;"><img border="0" src="http://4.bp.blogspot.com/-Tq-pvBZdbnA/U4ZOoXcpOaI/AAAAAAAABiw/Hl4dXGmUE-Q/s320/Filipa_Scarpa_Documental-April_Portugal_2014.jpg" /></a><br />
Although the mosquito and midge swarms studied scientifically are lot smaller than locust and grasshopper swarms, in the wild they can still be pretty impressive. The picture on the right is a "mosquito tornado" photographed by <a href="http://anafilipascarpa.blogspot.se/2014/05/mosquitoes-tornado-story-soon.html?spref=tw">Filipa Scarpa</a>. I have no idea what the mosquitos are doing here, but its pretty amazing.<br />
<br />
If you have any more insect swarms you think I should cover in the guide, tell me. The deadline is the end of the month.David Sumpterhttp://www.blogger.com/profile/09916867606281043665noreply@blogger.com0tag:blogger.com,1999:blog-33810541359136784.post-4320567620562669892014-05-29T22:51:00.003-07:002014-05-30T04:36:33.730-07:00Approaches to collective motion<div class="MsoNormal">
<span lang="EN-GB">One of the fantastic things about studying
collective behaviour is the varying backgrounds of the researchers involved. I
am a great believer that there is no unique way of looking at science. The
more perspectives we have the more chance we have of understanding the essence of a problem. </span><span lang="EN-GB">Many of Tuesday's talks at the </span><a href="http://www.collectivemotion2014.net/program">Interaction networks and collective motion in swarms, flocks and crowds</a> meeting really captured this
diversity. They were focussed on the 'collective motion' problem of describing how fish and birds move in groups.</div>
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<tr><td style="text-align: center;"><a href="https://pbs.twimg.com/media/BauyLjwIIAAba5Q.png:large" imageanchor="1" style="clear: right; margin-bottom: 1em; margin-left: auto; margin-right: auto;"><img border="0" src="https://pbs.twimg.com/media/BauyLjwIIAAba5Q.png:large" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Information transfer through a fish school. <br />
Work from Iain Couzin's lab</td></tr>
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It started with <a href="http://icouzin.princeton.edu/collective-motion-and-decision-making-in-animal-groups/">Iain Couzin</a> presenting his recent work on interaction
networks in fish. His research group have been able to reconstruct the visual
network of schools of fish, understanding who is following who. Iain, who was
one of the leading people in developing the classic self-propelled particle
like models of collective motion, suggested that the best way to understand
information transfer in these groups is through the networks and not
necessarily by building particle models. One of the ideas underlying this approach is to use <a href="http://www.richardpmann.com/research.html">machine learning to find models that best predict the patterns in the data</a>. The next talk by
<a href="http://www.sg.ethz.ch/team/people/nperony/">Nicolas Perony</a> also advocated this approach. He is going to use multiple sensors to track the details of what meerkats are doing. Machine learning and "reality mining" will be used to understand these vast quantities of collected data.</div>
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<tr><td style="text-align: center;"><a href="http://www.movementandinteraction.co.uk/images/news_trajectory.png" imageanchor="1" style="clear: left; margin-bottom: 1em; margin-left: auto; margin-right: auto;"><img border="0" src="http://www.movementandinteraction.co.uk/images/news_trajectory.png" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Identifying leader follower behavior<br />
at the <a href="http://www.movementandinteraction.co.uk/">Giuggioli lab</a></td></tr>
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<span style="mso-ansi-language: EN-US; mso-bidi-font-weight: bold;">But there is still place left for 'traditional' approaches of understanding interactions between individuals. Daniel Schardosim Calovi’s talk was on trying to find the interaction rules for Tetra fish. These fish move about in a bursty way, one moving in front followed by another, and capturing these bursts poses new data analysis problems. </span>Maksym Romenskyy was also trying to identify the statistical physics of fish interactions. He showed how this approach might shed new light on attraction/repulsion interactions. <a href="http://www.ms.osakafu-u.ac.jp/~gutchi/">Tsuyoshi Mizuguchi </a>and <a href="http://www.bristol.ac.uk/biology/people/luca-giuggioli/index.html">Luca Giuggioli</a> were both concerned with identifying how alignment patterns change between individuals. </div>
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I really enjoy seeing all these different approaches in action and it is hard to summarize all the new results in a blog post. But the major thing that struck me was how much more exciting work there is to be done. We have solved a lot of problems in collective motion over the last 5 years, but there are still many new challenges.</div>
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David Sumpterhttp://www.blogger.com/profile/09916867606281043665noreply@blogger.com0tag:blogger.com,1999:blog-33810541359136784.post-831236305937143932014-05-18T11:54:00.002-07:002014-05-19T03:23:23.390-07:00The future of automation<div dir="ltr" style="text-align: left;" trbidi="on">
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<span style="font-family: inherit; line-height: 1.15; white-space: pre-wrap;">Depending on your perspective, technological development has been saving us from drudgery, or destroying our livelihoods, for centuries. From the very first domestication of animals we’ve been finding ways to perform tasks with less human action since civilisation began.</span></div>
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<span style="font-family: inherit;"><span style="color: black; vertical-align: baseline; white-space: pre-wrap;">Last week </span><a href="http://www.robots.ox.ac.uk/~mosb/" style="text-decoration: none;"><span style="color: #1155cc; text-decoration: underline; vertical-align: baseline; white-space: pre-wrap;">Dr. Michael Osborne</span></a><span style="color: black; vertical-align: baseline; white-space: pre-wrap;"> from the University of Oxford gave a presentation at the Institute for Futures Studies showing his predictions about which of us will be losing our jobs in the century to come. Michael, as an expert in Machine Learning, is interested in which jobs will be automated as a result of increasing artificial intelligence in the Big Data era. He and his colleagues have been impressed at the rapid pace with which tasks that were seen as impossible for computers to perform, such as driving a car or translating accurately between different languages have become almost routine.</span></span></div>
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<a href="http://3.bp.blogspot.com/-I8tpqTLRyHw/U3na9DTQhmI/AAAAAAAAAME/KnIKN9JzYjM/s1600/fig1.jpg" imageanchor="1" style="line-height: 1.15; margin-left: 1em; margin-right: 1em;"><img border="0" src="http://3.bp.blogspot.com/-I8tpqTLRyHw/U3na9DTQhmI/AAAAAAAAAME/KnIKN9JzYjM/s1600/fig1.jpg" height="377" width="400" /></a></div>
<span style="font-family: inherit; line-height: 1.15;"><span style="color: black; vertical-align: baseline; white-space: pre-wrap;">Machine Learning itself can be used to predict which tasks are ripe for automation. First they gathered data on the skills necessary to perform over 700 different jobs, such as social sensitivity, manual dexterity and creativity. A panel of experts was then asked to predict which of 70 specific jobs would be automatable in the near future. Using Gaussian process regression, Michael and his colleagues learned a relationship between the skills a job requires and the probability that a computer will be able to perform, and extrapolated this relationship to the 700 jobs the panel had not evaluated. </span><a href="http://www.oxfordmartin.ox.ac.uk/downloads/academic/The_Future_of_Employment.pdf" style="text-decoration: none;"><span style="color: #1155cc; text-decoration: underline; vertical-align: baseline; white-space: pre-wrap;">Their results</span></a><span style="color: black; vertical-align: baseline; white-space: pre-wrap;"> give us a view on which sectors of the economy will be most affected by the continued rise of artificial intelligence. The graph below shows, by sector, what proportion of jobs are at low, medium or high risk of being automated. In general, those jobs requiring the most </span><span style="color: black; font-style: italic; vertical-align: baseline; white-space: pre-wrap;">necessary </span><span style="color: black; vertical-align: baseline; white-space: pre-wrap;">social interactions and/or high level creativity appear to be safest from the coming tide of job losses, but none of us can rest too easy!</span></span><br />
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<span style="line-height: 18px; white-space: pre-wrap;">However, we shouldn’t be too distressed at this imminent redundancy. As Michael pointed out for example, while technological progress has reduced the workforce in agriculture from almost 40% of employment in 1900 to around 2% today, the total unemployment rate has barely changed. Technology has allowed society to move human labour to more productive areas. The results of Michael’s analysis also show that it is generally lower paid, lower skilled jobs that will be destroyed, giving hope that people will be able to move into better employment, if society provides them with the necessary skills.
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Nonetheless, Michael also showed examples of resistance to change, such as the guilds of Tudor England blocking the development of machines for making textiles in fear of their members livelihoods. The ever increasing rate of automation, and the subsequent need for people to continually adapt to new careers and find new skills presents society with a powerful challenge, that may require new social contracts, such as a guaranteed citizen’s income and much more investment in public education to solve. It will be exciting to see where this process takes us!<br />
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Richard Mannhttp://www.blogger.com/profile/13769786662205310175noreply@blogger.com0tag:blogger.com,1999:blog-33810541359136784.post-5936306056722713252014-05-13T11:44:00.003-07:002014-05-13T11:44:41.708-07:00Three days of separationThe idea that we are only six introductions away from any other person on this planet is both beautiful and compelling. It has inspired research, provided inspiration to a film starring Will Smith and even <a href="http://www.sixdegrees.org/">launched a charity</a>. According to <a href="http://arxiv.org/pdf/0803.0939.pdf">Microsoft researchers</a> it might also be true. They found that the that the average path length connecting 180 million Messenger users in 2008 was 6.6. That was before Facebook and Twitter took off. By now the path length has probably shrunk further.<br />
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<tr><td style="text-align: center;"><a href="http://2.bp.blogspot.com/-wE80ziMydDY/U3JW_akYtrI/AAAAAAAAAK0/WiY02GXDHnw/s1600/Greatcircle.jpg" imageanchor="1" style="clear: right; margin-bottom: 1em; margin-left: auto; margin-right: auto;"><img border="0" src="http://2.bp.blogspot.com/-wE80ziMydDY/U3JW_akYtrI/AAAAAAAAAK0/WiY02GXDHnw/s1600/Greatcircle.jpg" height="120" width="200" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Distance of Zurich residents to their friends.<br />from: <a href="http://www.researchgate.net/publication/241273410_Contacts_in_a_shrunken_world/file/9c9605283baa5c9d99.pdf">Axhausen, K.W. and A. Frei (2008) </a></td></tr>
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And it isn't just the internet that is shrinking the world. On Friday at the <a href="http://www.iffs.se/en/seminar/why-are-the-home-addresses-of-your-friends-causing-greenhouse-warming-3/#more-17985">Future Institute</a>, <a href="http://www.ivt.ethz.ch/people/axhausen/index_EN">Kay Axhausen</a>, showed that road travel times have halved over the last 50 years, that we dedicate up to 40% of our leisure time to visiting friends and meeting new people, and that these friends are spread over the entire world. In one study, Kay and his colleagues looked at the distance from Zurich residents and their friends. It isn't unusual anymore to have friends spread over 5 orders of magnitude. Kay argues that this effect isn't limited to Europeans and North Americans, citing recent data from Concepcion, Chile where people have similar friend-distance distributions as Europe. There are apparently a few die-hards who refuse to join the global-village, but they are becoming increasingly rare (as well as isolated).<br />
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But the thing that struck me most was the time scale of the links. A <a href="http://www.pnas.org/content/110/34/13774.full?tab=ds">recent paper in PNAS</a> looked at bus trips in Singapore. Kay and colleagues drew a line between people if they travelled on the same bus on the same day. In the figure above the red lines show a shared bus trip on Monday, the greens are trips together on Tuesday and a cyan are trips on Wednesday. The last picture are all the weekday trips put together. By Friday, all the people are now connected through shared trips.<br />
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It turned out that even by Wednesday all Singapore bus travelers were connected. There are just three days of separation between bus travelers.<br />
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A bus trip isn't enough time to make friends. But it is enough time to check out what other people are wearing, what mobile they are using, what newspaper they are reading and even to overhear a few opions about the world. It is enough time for all sorts of interesting social information to spread. This result would have appealed to Stanley Milgram, whose small-world study first led to the 6-degrees idea. Cities fundamentally change <a href="http://www.amazon.com/The-Individual-Social-World-Experiments/dp/1905177127">the individual's social world</a> in many different ways, not least in the time it takes for us to connect to each other.David Sumpterhttp://www.blogger.com/profile/09916867606281043665noreply@blogger.com0tag:blogger.com,1999:blog-33810541359136784.post-29150846145158379602014-05-06T09:39:00.000-07:002014-05-06T09:39:17.664-07:00Science hasn't ended yet….<div class="MsoNormal">
<span style="font-family: inherit;">Twenty years ago the journalist John Horgan wrote a book called the ‘<a href="http://www.amazon.com/The-End-Science-Knowledge-Scientific/dp/0553061747">End of Science</a>’. This must be one of the best popular science book ever written. Instead of the usual sycophantic interviews and hyped up description what scientists do, Horgan employed a more investigative style of journalism. He met with scientist after scientist and argued with them that all they were doing was either pointless tying up of loose ends or applied engineering. The big scientific questions were all already answered by Darwin, Einstein, Feynman etc.<o:p></o:p></span></div>
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<tr><td class="tr-caption" style="text-align: center;">Picture from Robert Laughlin's <br />
<a href="http://large.stanford.edu/cartoons/universe/">collection of cartoons illustrating his ideas</a>.</td></tr>
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<span style="font-family: inherit;">It was this accusation that science is over, which <a href="http://large.stanford.edu/">Robert Laughlin</a> addressed in his <span lang="EN-GB"><a href="http://www.polacksbacken.uu.se/News/News/?tarContentId=309567"><span lang="EN-US" style="color: #0020dd;">Ångström lecture</span></a></span> in Uppsala. His hand drawn image shown on the right illustrated his main point. If you look in to the distance, like the character pointing towards the fantastic “frontier”, then it seems that all questions are answered. All the important things are answered by the beautiful view. On the other hand, if you ignore the view, like the other two characters in his drawing, and you instead look down at the detail of things nearby, then everything is a lot more difficult to comprehend. Science is just starting<o:p></o:p></span></div>
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<span style="font-family: inherit;">Laughlin's presentation built on a point first made in Philip Anderson's seminal paper that <a href="http://www.google.se/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&ved=0CCkQFjAA&url=http%3A%2F%2Fwww.ph.utexas.edu%2F~wktse%2FWelcome_files%2FMore_Is_Different_Phil_Anderson.pdf&ei=tgtpU_j2O-z3yAOQ1IH4BA&usg=AFQjCNHlECGkkkfNN7mZtjRuHeAUPYDxcA&bvm=bv.66111022,d.bGQ">'more is different</a>'. The idea is that at all levels of physical, chemical, biological and social organization, we cannot expect to use simple extrapolations of observations from the level of organization below to understand the level above. For example, the rigidity of ice isn't found in a description of a single water molecule. Similarly, we can’t claim to understand the internet just because we know how to program a computer. The combination of applications and content is more than the sum of the individual lines of code.<o:p></o:p></span></div>
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<span style="font-family: inherit;">Laughlin goes one step further in this argument. He claims that "all laws of physics are discovered, and none are derived from first principles”. He argues that we can't sit down and reason our way to physical relationships from what we know already at the level below. Instead, we need to invent new “emergent” ways of describing systems, which combined with experiment allow us to understand things better. Each new law of emergent organisation must be understood in its own terms. This means that even if projects like string theory and grand-unification were to work, they do not provide much additional information about the rest of the Universe.<o:p></o:p></span></div>
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<span style="font-family: inherit;">Some of Laughlin’s argument is common sense to anyone working outside physics (and to many people working inside physics too). No one would seriously claim that we can better understand animal biology using particle physics. But other parts of the argument require serious consideration by all scientists, not just physicists. For example, is genetics really relevant for understanding social behavior? Many biologists would argue that it is the most important tool we have, but maybe it requires us to step up over too many scales?<o:p></o:p></span></div>
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<span style="font-family: inherit;">I think what Laughlin is trying to argue is that Science can’t be thought of as ending, because the so-called great scientific laws of Darwin, Newton etc. are ‘just’ examples of discoveries of useful regularities. While they are great discoveries, they are no more fundamental than finding out that stacking objects makes certain shapes of pyramid or that water freezes in the same way as other chemicals. They are no more fundamental than finding out that connecting up a load of computers results in a massive change in human society. Not every discovery is equal---Laughlin received a Nobel prize in 1998 for his “<a href="http://www.nobelprize.org/nobel_prizes/physics/laureates/1998/press.html">discovery of a new form of quantum fluid</a>”---but no discovery is more fundamental than any another.</span></div>
David Sumpterhttp://www.blogger.com/profile/09916867606281043665noreply@blogger.com3tag:blogger.com,1999:blog-33810541359136784.post-37041843497007256092014-04-28T08:28:00.000-07:002014-04-28T08:28:09.460-07:00Learning to play.<div>
In 2007, the Swedish gambling agency ran a simple gambling game called LIMBO. Gamblers were invited to stake 10 kronor on a number of their choice between 1 and 99,999. The person choosing the smallest number that no-one else chose is the winner: taking home a prize of around 100,000 kronor. What number would you choose?</div>
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<tr><td class="tr-caption" style="text-align: center;"><a href="https://editorialexpress.com/cgi-bin/conference/download.cgi?db_name=GAMES2012&paper_id=486">Poisson-Nash equilibrium for an average of 53,783 players</a></td></tr>
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When I played the game at <a href="https://sites.google.com/site/karlerikmohlin/">Erik Mohlin</a>'s interesting and engaging <a href="http://www.iffs.se/en/seminar/learning-by-imitation-in-games-theory-field-and-lab-2/">seminar at the Institute for Futures Studies last Friday</a>, I chose '1'. A bit naive, maybe, and quite a few others thought the same way. The winning number in an audience of about twenty of us was '5'. While the game is not straightforward, it is possible to determine a probabilistic equilibrium strategy. If all players pick numbers according to the distribution on the right, then no player can improve their performance by changing away from this distribution. Note that the probability of choosing large numbers is not zero, but it is very very small. </div>
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The question Erik asked was how people learn to play the game. It is unlikely that everyone worked out the best strategy using stochastic game theory. Indeed, in the first week in Sweden people didn't play so well. Like me, they clustered around very low numbers, maybe not realizing that everyone else would do the same. But over time the distribution stretched out and they collectively took a strategy close to the optimal. Winning numbers after two months of play were between 162 and 3590. </div>
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How do people get collectively better at games line LIMBO? This question was tested on <a href="http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.183.1649&rep=rep1&type=pdf">data from a lab experiment</a>, where smaller numbers of people played a similar game. Erik and his co-workers found that the explanation that best fit the data was a form of imitative learning, where the players would look at previous winners' numbers, and increase their probability of choosing a number the same or near to the winners. Through this learning they eventually arrive at the equilibrium shown above, both in the model and in the data. Imitative learning is quick way of finding out how to play a game well.</div>
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The fact that imitative learning works so well for game playing is an important insight for basic economic theory. Economist often argue about if and when the <a href="http://collective-behavior.blogspot.se/2013_12_01_archive.html">equilibrium of a game is useful for predicting the behavior of real people</a>. In this case it seems to be very useful. The equilibrium is quickly reached through a simple process of imitation. </div>
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<a href="http://1.bp.blogspot.com/-ywZ1nDwHvbU/U1usgSmtgBI/AAAAAAAAAKE/YbX3LamAFME/s1600/Limbo.jpg" imageanchor="1" style="clear: right; float: right; margin-bottom: 1em; margin-left: 1em;"><img border="0" src="http://1.bp.blogspot.com/-ywZ1nDwHvbU/U1usgSmtgBI/AAAAAAAAAKE/YbX3LamAFME/s1600/Limbo.jpg" height="129" width="320" /></a><b>But…….. </b>The Swedish gambling agency closed LIMBO about 3 months after it started because they believed people were using syndicates to cheat. It isn't hard to see why. The winning numbers were usually in an interval 1000 to 3500. So an investment of 25,000 kronor by a consortium was almost guaranteed to win the 100,000 kronor first prize. If there was more than one consortium then this would drive the winning numbers up and maybe the consortiums would start to lose. But it is clear that the game becomes unfair for honest, single players. If you can read Swedish, it is quite amusing to read the press releases from Svenska Spel as they first <a href="http://media.svenskaspel.se/sv/2007/01/26/varldspremiar-for-nya-nummerspelet-limbo/">introduce the game as the result of 5 years research</a>, then provide some <a href="http://media.svenskaspel.se/sv/2007/02/26/succe-for-nya-nummerspelet-limbo/">tips on how to pick your numbers</a>, then finally admit that t<a href="http://www.svd.se/nyheter/inrikes/svenska-spel-stoppar-limbo_1074245.svd">he game was against gaming laws all along</a>. </div>
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I think this real-life outcome raises just as many interesting economic questions as the original game. As soon as the game was introduced, independent gamblers built a syndicate to make sure they took home a profit. This is where the collective behavior comes in. Groups of independent actors quickly self-organizing to manipulate the market. Understanding how groups form and manipulate these games is a much harder problem to study scientifically. But if related to the behavior of economic agents such as banks and other financial institutions over the last few years, it is certainly a no less important a question to answer. </div>
David Sumpterhttp://www.blogger.com/profile/09916867606281043665noreply@blogger.com2tag:blogger.com,1999:blog-33810541359136784.post-63894491007441688942014-04-22T22:25:00.000-07:002014-04-22T22:25:43.912-07:00Ants are just as clever (and stupid) as people.Last week I found out that <a href="http://www.takaosasaki.com/">Takao Sasaki</a> was one of the winners of this year's <a href="http://www.cognitivesciencesociety.org/about_awards_glushko_overview.html">Glushko prize</a> for cognitive science. The prize is awarded by the Cognitive Science Society, whose overall aim is to further understanding of the human mind. Given this, it was very gracious of them to give the prize to Takao. His PhD thesis wasn't really about the human mind. Instead, it was dedicated to showing that rock ants are just as smart as humans. Or, when working as a colony, possibly even smarter.<br />
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<tr><td style="text-align: center;"><a href="http://4.bp.blogspot.com/-ea0lrPjN3N0/U1bJ_hrDi7I/AAAAAAAAAJc/kov8kvvET7Y/s1600/Transport.jpg" imageanchor="1" style="clear: right; margin-bottom: 1em; margin-left: auto; margin-right: auto;"><img border="0" src="http://4.bp.blogspot.com/-ea0lrPjN3N0/U1bJ_hrDi7I/AAAAAAAAAJc/kov8kvvET7Y/s1600/Transport.jpg" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">One ant carries another to her new home</td></tr>
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Takao started with rationality. Over the last decade <a href="http://www.scientificamerican.com/article/the-science-of-irrational/">economists have been gradually discovering</a>, what any bloke in the pub could have told them for free, that humans are not rational. For example, one thing retailers often do to fool us irrational mortals is place out a number of unattractive decoy products which make the product they want you to buy seem like a better deal. Takao <a href="https://www.dropbox.com/s/f9yiyssqy8ewyhb/Sasaki%20%26%20Pratt%202011%20Rationality.pdf">did the same with his ants</a>. He found that individual ants changed their preferences for the nest they would like to live in when offered an additional option. Ants are just as malleable as we are. But it turned out that the ant colony as a whole was not swayed by irrelevant options. A bit like when you come home from a shopping trip and your family asks you "why the hell did you buy that?", the colony is a whole is more sensible than any of the individuals in it.<br />
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<tr><td class="tr-caption" style="text-align: center;">Individual ants can choose between a good and a bad nest <br />site, but have difficulty with eight. Colonies have no <br />problems with either set up. </td></tr>
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One explanation for irrationality in individual ants may lie in <a href="https://www.dropbox.com/s/46rsw9kp1tiqzuo/CurrentBiologySasakiPratt.pdf">differences in cognitive capacity between groups and individuals</a>. In his next experiment, Takao tested how individuals and colonies performed when offered large numbers of potential homes, some good and some bad. The colonies seldom chose a bad nest, but the individuals did so nearly 50% of the time. When compared to groups, individuals are not only irrational but downright bad decision-makers.<br />
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So groups are better than individuals? The crowd is always wise? Well, not always. Next Takao looked at how decision-making difficulty affects the ability of colonies to choose the best of two nests. <a href="https://www.dropbox.com/s/katl4dag3lcc5rg/PNAS-2013-Sasaki-1304917110.pdf">He showed that</a>, as in his earlier work, the colony was better than the individual at choosing when a difficult decision had to be made. But when the decision was straightforward, and one of the potential homes was a lot better than the other, the colonies got it wrong more often than the individuals.<br />
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Takao's <a href="https://www.dropbox.com/s/k5n8ur1rzjd9bi9/Biol.%20Lett.-2013-Sasaki-.pdf">latest paper is on learning</a>. When ants repeatedly experience, for example, very light nests (which they like), then they put a premium on very dark nests. On the other hand, if they experience, nests with large entrances (again something they don't line), then they put a premium on narrow entrances. Again the ants are a bit like us.<br />
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Takao's PhD supervisor and co-author on the above work is <a href="http://www.public.asu.edu/~spratt1/index.html">Stephen Pratt</a>, who I have known and worked with for many years. Stephen and my work together focussed more on the mechanisms these ants use to make good group decisions. Takao's thesis really takes a whole new direction by testing ideas from cognitive science on ants, and I think the award is very fitting. Well done!<br />
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And don't worry if you happen to be human. One day we will prove that we are smarter than ants, but we are still a long way off.<br />
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<br />David Sumpterhttp://www.blogger.com/profile/09916867606281043665noreply@blogger.com0tag:blogger.com,1999:blog-33810541359136784.post-64245680867002137232014-04-10T16:32:00.000-07:002014-04-10T16:33:36.958-07:00What is a complex system?This week I started teaching the course 'Modelling Complex Systems'. I decided this year to make video lectures for the course. In the first one, I define complex systems. This is not an easy thing to do. There is no real recognized definition, and the <a href="http://en.wikipedia.org/wiki/Complex_system">wikipedia page</a> is pretty confusing. Complex systems are systems that are, er, well, complicated (although even this obvious statement <a href="http://www.cadmusjournal.org/node/362">is often argued against</a>)<br />
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My answer is simple, I just show a lot of systems which make complex looking patterns and say "complex" a lot. A similar (but more eloquent) answer is also given by Melanie Mitchell in her excellent <a href="http://www.complexityexplorer.org/">complexity explorer</a> course. <br />
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I do have one little twist, and that is that a complex system is one in which you can use mathematical modeling to better understand it. This leads me nicely to my second lecture: what is mathematical modeling? This question I have thought about a lot, and I think here I give a reasonably useful and general explanation of why we use mathematical models. Models are used for one of four reasons:<br />
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1, Explain data as simply as possible.<br />
2, Link together levels of explanation.<br />
3, To provide detailed descriptions. <br />
4, To predict future outcomes.<br />
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Complex systems are most associated with number 2. Have a look at the video and see what you think.</div>
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I will hopefully be putting all my lectures up on a webpage in the future. One request I have now is that if anyone can suggest good articles on which the students can base mini-projects please tell me. The students on this course tend to be exceptionally good at modeling and mathematics, and highly motivated. So any 'complex systems' models that can be implemented and tested in 4 weeks would be much appreciated.David Sumpterhttp://www.blogger.com/profile/09916867606281043665noreply@blogger.com2tag:blogger.com,1999:blog-33810541359136784.post-46706071740773952032014-04-09T03:19:00.002-07:002014-04-09T04:48:13.767-07:00Why care for your kids when someone else will do it for you? Its been a while since I wrote a blog post, and this mainly because I have been lost in my own thoughts during my 'sabbatical' in Sydney. But I managed to raise myself from self-indulgence and go to a really nice seminar on Friday by <a href="http://sydney.edu.au/science/biology/socialinsects/profiles/ros-gloag.shtml">Ros Gloag</a>. Ros is doing a Postdoc in <a href="http://sydney.edu.au/science/biology/socialinsects/">Madeleine and Ben's</a> social insect group in Sydney, after finishing her PhD together with <a href="http://users.ox.ac.uk/~kgroup/people/alexkacelnik.shtml">Alex Kacelnik</a> in Oxford.<br />
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Ros spent her PhD studying shiny cowbirds and chalk-browed mockingbirds in South America. These cowbirds pose something of an evolutionary puzzle, because they are such blatant parasites. What the cowbirds do is hop in to the mockingbirds nest, lay an egg and then fly away. The mockingbirds don't like this. If they catch the cowbirds (which they often do) they attack them pretty fiercely (see a bird get beaten up but still lay her egg in a video below). This doesn't seem to stop the cowbirds laying an egg, <a href="http://www.sciencedirect.com/science/article/pii/S0003347213004077">although it does stop the cowbirds damaging any of the mockingbirds own eggs</a>.<br />
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But the strange thing is that the egg left by the cowbird looks very different from the mockingbird's own eggs. Why doesn't the mockingbird just destroy it and throw it out? Ros showed that <a href="http://rspb.royalsocietypublishing.org/content/279/1734/1831">mockingbird eggs in nests containing cowbird eggs were less likely to be damaged or destroyed</a>. This is because when other cowbirds come along and attack the nests, they end up damaging the cowbird eggs which are already there rather than the mockingbird's own eggs.<br />
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Once the all the eggs hatch, host birds continue to look after both the cowbird and their own chicks. One clue to why the hosts do this can be found in the vocal recordings of the cowbird chicks. The cowbird appears to mimic the calling of groups of hungry chicks, <a href="http://www.sciencedirect.com/science/article/pii/S000334721300198X">producing a general enough sound to fool a range of different host species</a>. This causes the parents to collect even more food than they usually would, which the cowbird laps up.<br />
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Ros' thesis is a beautiful example of how the behavioral ecology approach helps us understand the evolution of host and parasite interactions. She has nicely combined the cycle of experiment, thinking about what the experiment implies, building a theory, and then testing it with a new experiment.<br />
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There is a danger in the behavioral ecology approach that experiments are done until one of them identifies an advantage for the host, at which point we stop and congratulate natural selection on its amazing power of finding a balance. This can make me a bit suspicious. In Ros' case there are still a few open ends, but I think this is to her credit. Instead of finding a full answer, her research documents the subtleties of hosts and parasite relationships.<br />
<br />David Sumpterhttp://www.blogger.com/profile/09916867606281043665noreply@blogger.com0tag:blogger.com,1999:blog-33810541359136784.post-69547378060863593882014-02-21T23:34:00.002-08:002014-02-21T23:34:57.730-08:00About 100 flying particlesDaniel Strömbom and myself are organizing a symposium at the coming <a href="http://ecmtb2014.org/">European Conference on Mathematical and Theoretical Biology</a>. The title is the <a href="https://sites.google.com/site/collectivemotionof100particles/">collective motion of about 100 particles</a>.<br />
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The symposium is about <a href="http://arxiv.org/abs/1010.5017">collective motion</a> of animals and cells. Models in which we describe how individuals form groups, move together and form spectaculr patterns. The title captures what we think is a central mathematical problem with these models. Mathematicians are good at solving problems that involve two or three interacting objects and it is good at solving problems that involve an infinite number of objects, where everything blurs in to a continuum. It is not very good at dealing with 100s and 1000s of interacting objects. It is exactly these numbers which are typical for interesting animal flocks, like starlings and human crowds.<br />
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We have four invited speakers <span style="background-color: white; font-family: 'Times New Roman', serif; font-size: 12pt; line-height: 18px;"><a href="http://www.sjc.ox.ac.uk/660-4553/Dr-James-Anderson.html">James Anderson</a>, </span><span style="background-color: white; font-family: 'Times New Roman', serif; font-size: 12pt; line-height: 18px;"><a href="http://www.maths.dundee.ac.uk/reftimie/">Raluca Eftimie</a>, </span><span style="background-color: white; font-family: 'Times New Roman', serif; font-size: 12pt; line-height: 18px;"><a href="http://www.mpipks-dresden.mpg.de/~prom/index.html">Pawel Romanczuk</a> and <a href="http://people.maths.ox.ac.uk/yatesc/">Kit</a></span><span style="background-color: white; font-family: 'Times New Roman', serif; font-size: 12pt; line-height: 18px;"><a href="http://people.maths.ox.ac.uk/yatesc/"> Yates</a>, all of who have very different approaches to the problem. We hope to create a lively discussion and debate afterwards and start to think about how to tackle this problem. W</span>e are now looking for a few more contributed talks. Please send an abstract to <a href="mailto:strombom@math.uu.se">Daniel</a> if you are interested.<br />
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<br />David Sumpterhttp://www.blogger.com/profile/09916867606281043665noreply@blogger.com0tag:blogger.com,1999:blog-33810541359136784.post-46023393907848079842014-02-08T02:34:00.003-08:002014-02-08T03:10:42.285-08:00Facebook vs Princeton vs Sumpter<div class="MsoNormal" style="mso-layout-grid-align: none; mso-pagination: none; text-autospace: none;">
<span style="font-family: inherit;">In an <a href="http://collective-behavior.blogspot.com.au/2013/11/logistic-growth-in-human-world.html"><span style="color: #0020dd;">earlier post</span></a> I wrote about how useful the
logistic growth equation is in modeling different social phenomena. I thought
it was fun then, when a logistic growth fitting war broke out between two
Princeton PhD students and some Facebook researchers. John Canarella and
Joshua Spechler put up a <a href="http://arxiv.org/abs/1401.4208"><span style="color: #0020dd;">paper</span></a> on arXiv fitting an adapted SIR disease
model to My Space and Facebook searches on Google. Their SIR model is
essentially two logistic growths put together: one for infection with Facebook
and one for recovery afterwards. They predicted that Facebook was now facing a
'recovery' phase where people will stop using it, and this abandonment would
spread through social infection. <o:p></o:p></span></div>
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<span style="font-family: inherit;">This result was reported in
several places in the <a href="http://www.independent.co.uk/life-style/gadgets-and-tech/facebook-is-an-infectious-disease-and-will-lose-80-of-users-by-2017-say-researchers-9079342.html"><span style="color: #0020dd;">media</span></a>, despite not having gone through any
peer-review. Facebook researchers were fast to do their peer review for
them, pointing out that a whole range of search indicators show <a href="https://www.facebook.com/notes/mike-develin/debunking-princeton/10151947421191849"><span style="color: #0020dd;">that Princeton is in terminal decline</span></a>. The
main problem for the Princeton study, according to Facebook, is that they don't
show any causation, just a correlation. <o:p></o:p></span></div>
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<span style="font-family: inherit;">In my opinion, the Facebook
researchers review fails to seriously address the possibility that we might be
seeing a 'recovery' from Facebook. Unlike Princeton or Air (their other
example), Facebook is actually a social media, and its success has spread
through a social contagion. There is therefore an underlying causal reason for
applying an SIR model to Facebook. Where the Princeton study is limited,
however, is in the data set it uses. In order to do this study properly access
is needed to the log-in events for the users of Facebook. Data which Facebook
have, of course, and I can't imagine they are about to hand over to two
graduate students at Princeton.<o:p></o:p></span></div>
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<span style="font-family: inherit;">If Facebook do want to test
whether they are in decline or not using log-in data, I can recommend the
method Richard Mann and I developed to look at <a href="http://rsif.royalsocietypublishing.org/content/10/85/20130466"><span style="color: #0020dd;">audience applause</span></a>. We use exactly the same
model as the Princeton guys, but fit it on individual events. Substitute hand
claps for 'likes' and Facebook can find out how its going for them.<o:p></o:p></span></div>
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<div class="MsoNormal" style="mso-layout-grid-align: none; mso-pagination: none; text-autospace: none;">
<a href="http://1.bp.blogspot.com/-UoBGTU6rYfQ/UvYH6JlZH3I/AAAAAAAAAG8/EA824Yzenn0/s1600/followers.jpg" imageanchor="1" style="clear: right; float: right; margin-bottom: 1em; margin-left: 1em;"><span style="font-family: inherit;"><img border="0" src="http://1.bp.blogspot.com/-UoBGTU6rYfQ/UvYH6JlZH3I/AAAAAAAAAG8/EA824Yzenn0/s1600/followers.jpg" height="240" width="320" /></span></a><span style="font-family: inherit;">Anyway, all this is a
digression. I thought it might be illuminating to do a study of my own meteoric
rise in popularity on Twitter. In January, I surpassed 100 followers. I am
still somewhat behind another collective behavior Twitterer, <a href="http://www.theswarmlab.com/"><span style="color: #0020dd;">Simon Garnier</span></a>,
who just announced his passing 1001 followers. On the right I show my increase
in followers and I fit the logistic equation to the data. I was shocked to find out that I have already entered a 'recovery' phase. According to the fit, my
following has leveled off.<o:p></o:p></span></div>
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<span style="font-family: inherit;">Luckily, none of these
results are statistically significant and my ultimate following could be
anywhere between 120 and 7 billion. So keep following!<o:p></o:p></span></div>
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<span style="font-family: inherit;">If anyone out there wants
to check their own following in Twitter, I include the Matlab code to do this
below. All you have to do is add the days since starting and along with the
number of additional followers you have got on those days, and you too can know
if you too are still a social contagion.<o:p></o:p></span></div>
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David Sumpterhttp://www.blogger.com/profile/09916867606281043665noreply@blogger.com4tag:blogger.com,1999:blog-33810541359136784.post-79518824671896358742014-01-24T00:32:00.001-08:002014-01-24T00:34:46.255-08:00Explaining things with flow<div class="MsoNormal">
This week our group’s first full <a href="http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0086468">paper on modelling socio-economic systems</a>
came out in PLoS One. The idea for this article came up when I saw<b> <a href="http://www.youtube.com/watch?v=hVimVzgtD6w">Hans Rosling’s presentations</a></b> of <a href="http://www.gapminder.org/">Gapminder</a>. When you see how Rosling's bubbles
representing countries float up from poverty and low life expectancy towards a better world you can’t
help be inspired by the power of data.</div>
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<span lang="EN-GB">Watching Rolsing’s videos, I also
thought about fish movements! We have been using dynamical systems and Bayesian
model selection to identify the models which best fit the rules of motion of
fish. If we can think of countries as fish then we could use the same
methods to find the rules of motion of countries in a socio-economic space, rather than a fish tank.<o:p></o:p></span></div>
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<span lang="EN-GB">There turned out to be quite a lot of
differences, as well as similarities, between fish and countries. But keeping
this initial analogy in mind, Shyam Ranganathan and Viktoria Spaiser have <a href="http://cran.r-project.org/web/packages/bdynsys/">developed a toolbox in R</a> for finding
the best set of differential equation models that describe socio-economic change.
In the paper, we apply these methods to democracy and economic growth. You can
see more about this in the video on the right. Not quite up to Rosling enthusiastic
standard of <a href="https://www.youtube.com/watch?v=BkSO9pOVpRM">simplifying things</a>, but I hope it illustrates the idea behind the paper.<o:p></o:p></span></div>
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<span lang="EN-GB">We are now applying this method to look at
the demographic transition, the changes in cultural values across the world, as
well as segregation in schools. Most of these projects are based at the <a href="http://www.iffs.se/">Futures Institute in Stockholm</a>. The
idea in the paper is to present the tools, rather than make predictions. But we
hope that future work will lead to useful insights in to how the world is
changing and what we should do about it. </span><br />
<span lang="EN-GB"><br /></span>
<span lang="EN-GB">Please contact us if you have data
that you think can be analysed using this method. <o:p></o:p></span></div>
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David Sumpterhttp://www.blogger.com/profile/09916867606281043665noreply@blogger.com0tag:blogger.com,1999:blog-33810541359136784.post-18774490193376099812014-01-20T16:47:00.001-08:002014-01-21T00:15:29.545-08:00Anti-social extinction<div class="MsoNormal">
<span lang="EN-GB">During a recent trip to New Zealand, I
visited a couple of bird conservation projects. One was for the <a href="http://www.wildkiwi.co.nz/kiwibackstagepass">rarest of thefour species of Kiwi birds</a>, the other for <a href="http://www.penguinplace.co.nz/">yellow-eyed penguins</a>. Both these
conservation projects are doing an amazing job keeping the animals living in
their natural environment, while allowing tourists like me to get a <a href="http://www.tandfonline.com/doi/abs/10.1080/09669580008667348#.Ut3ATv3Ojos">look atthem and develop some insight in to conservation issues</a>.<o:p></o:p></span></div>
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<table cellpadding="0" cellspacing="0" class="tr-caption-container" style="float: left; margin-right: 1em; text-align: left;"><tbody>
<tr><td style="text-align: center;"><a href="http://4.bp.blogspot.com/-eHNi7V8Y9uU/UGXaR4LoirI/AAAAAAAACPs/okcd2QmMNw0/s1600/yellow+eyed+penguins+Penguin+yellow+eyed+penguin+endangered+species+emperor+penguin+king+penguin+facts+about+penguins+information+about+penguins+beautiful+amazing+animal+pictures.jpg" imageanchor="1" style="clear: left; margin-bottom: 1em; margin-left: auto; margin-right: auto;"><img border="0" src="http://4.bp.blogspot.com/-eHNi7V8Y9uU/UGXaR4LoirI/AAAAAAAACPs/okcd2QmMNw0/s1600/yellow+eyed+penguins+Penguin+yellow+eyed+penguin+endangered+species+emperor+penguin+king+penguin+facts+about+penguins+information+about+penguins+beautiful+amazing+animal+pictures.jpg" height="252" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">A yellow-eyed penguin couple and baby penguin.</td></tr>
</tbody></table>
<span lang="EN-GB">My wife commented that it was ironic that,
given I prefer group-living animals, we were visiting two anti-social species.
Kiwis pair for life and jointly care for one egg at a time. But when the egg
hatches they first ignore the newly hatched bird, and when it they gets bigger
they just chase it away. The yellow-eyed penguins also form long-standing couples (although homosexuality, divorce and season long infidelities do occur) and
invest in joint parental care. But once their offspring is big enough to fend
for itself, it has to find its own territory.<o:p></o:p></span></div>
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<tr><td style="text-align: center;"><a href="https://encrypted-tbn2.gstatic.com/images?q=tbn:ANd9GcTET86z6vVWT3Gm_ZqMTmydozdpEBUlfBUIV_cYGvTQGbKConhb7du4yFa-" imageanchor="1" style="clear: right; margin-bottom: 1em; margin-left: auto; margin-right: auto;"><img border="0" src="https://encrypted-tbn2.gstatic.com/images?q=tbn:ANd9GcTET86z6vVWT3Gm_ZqMTmydozdpEBUlfBUIV_cYGvTQGbKConhb7du4yFa-" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">A group of blue-eyed penguins</td></tr>
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<span lang="EN-GB">This anti-social behaviour makes
conservation difficult, simply because more space is required for a sustainable
population. I was struck most by this when we saw a colony of blue-eyed
penguins on a nearby cliff. These birds also form breeding pairs, but are happy
to live in close proximity to other blue-eyes and a vast array of seagulls.
Blue-eye penguins are more numerous and wide spread in New Zealand and,
although we shouldn’t become blasé, they are not endangered.<o:p></o:p></span></div>
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<span lang="EN-GB">What I hadn’t thought of before is that the
difficulty of conserving solitary-living species could help explain the evolution
of sociality. Animals that are difficult to conserve are prone to
extinction when their environment changes. Penguins that tolerate each other
have to share local nesting resources, but if space suddenly becomes limited they
don’t waste time and energy fighting with each other. Territorial penguins
might be able to chase off more tolerant penguins and dominate the best nests,
but if their territory comes under attack by a predator, for example, they are not welcome at
their neighbours place. <o:p></o:p></span></div>
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<span lang="EN-GB">Developing an argument about evolution of territoriality requires a
model defined in terms of selfish individuals, not species success. My evolutionary penguins are playing some form of a ‘tragedy of the commons’ game, where in a stable environment
selective pressure acts to make them more territorial. In an unstable
environment, where territories can suddenly become unusable, selection may favour
greater tolerance. When danger arises penguins that tolerate each other can
congregate in the few available sites. Provided that penguins can only migrate
locally, then local extinctions of territorial penguins who start fighting over the few available resources can lead to the
evolution of greater tolerance for neighbors. </span></div>
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<span lang="EN-GB"><br /></span></div>
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The penguin model I sketch above is related to the idea of <a href="http://www.jstor.org/stable/10.2307/2459020">r and K selection</a> popular in the 1970s and 80s, and now replaced by more <a href="http://www2.hawaii.edu/~taylor/z652/Reznicketal.pdf">general life history models</a>. In environments where everything is stable (limited by the carrying capacity K) it is better to defend your territory. When territories are shifting (growth rate r is more important) then defense of these territories is less important and it is more important to do well in the space that can be found. I have to admit I don't know much about the literature that links together evolution of co-operation with <a href="http://www.jstor.org/stable/2389364">life history strategies</a>. I found <a href="http://www.csun.edu/~dgray/BE528/HatchwellKomdeur2000Coop.pdf">one review</a> of co-operation (a bigger step than just tolerating each other). Maybe people working on the evolution of co-operation should stop <a href="http://www.thisviewoflife.com/index.php/magazine/articles/richard-dawkins-edward-o.-wilson-and-the-consensus-of-the-many">bickering over nothing</a> and get a bit more biological detail in their models.<br />
<br />
Disclaimer: I don't think my penguin model is necessarily a good description of what actually happened in real penguins. It turns out that <a href="http://rspb.royalsocietypublishing.org/content/276/1658/815.short">modern yellow-eyed penguins may well have arrived with humans in New Zealand</a>.<br />
<br /></div>
David Sumpterhttp://www.blogger.com/profile/09916867606281043665noreply@blogger.com0tag:blogger.com,1999:blog-33810541359136784.post-16379155913359068102014-01-17T00:35:00.000-08:002014-01-17T00:43:09.371-08:00A picture of two penguins<!--[if gte mso 9]><xml>
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<span lang="EN-GB">I have been having a bit of an extended
holiday over Christmas till now. Since New Year I have been in Australia and New
Zealand. F</span>rom Monday, I will be in Sydney on sabbatical until the start of April. Visiting <a href="http://sydney.edu.au/science/biology/animalbehaviour/people.shtml">Ashley Ward</a> and his growing research group.<br />
<br />
And I will be back to blogging soon. We have a paper
coming out on Monday on our dynamical systems methods for studying socio-economic systems, I am going to write something inspired by my holiday about why
solitary living animals might be more at risk of extinction than those living
in groups. I have had a couple of students finish interesting projects, one on
evolutionary game theory of poker and one on studying the pop charts, which I
want to write about. And I might even do an analysis of my Twitter following
(still quite low, but growing).</div>
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<br /></div>
<div class="MsoNormal">
<table cellpadding="0" cellspacing="0" class="tr-caption-container" style="float: right; margin-left: 1em; text-align: right;"><tbody>
<tr><td style="text-align: center;"><a href="http://1.bp.blogspot.com/-XxPofQpEv5Q/Utjp-j6vTRI/AAAAAAAAAFk/X29Pt3yg6vY/s1600/IMG_1041.JPG" imageanchor="1" style="clear: right; margin-bottom: 1em; margin-left: auto; margin-right: auto;"><img border="0" src="http://1.bp.blogspot.com/-XxPofQpEv5Q/Utjp-j6vTRI/AAAAAAAAAFk/X29Pt3yg6vY/s1600/IMG_1041.JPG" height="240" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Photo: Elise Sumpter</td></tr>
</tbody></table>
<span lang="EN-GB">In the meantime, here is a picture of a
couple of </span><a href="http://www.penguinplace.co.nz/">yellow-eyed penguins</a>. Sadly, two of just 4000 left on the planet. </div>
<br />David Sumpterhttp://www.blogger.com/profile/09916867606281043665noreply@blogger.com0tag:blogger.com,1999:blog-33810541359136784.post-72147665083697032162013-12-18T12:21:00.000-08:002013-12-18T12:21:37.179-08:00The rationality paradox<table cellpadding="0" cellspacing="0" class="tr-caption-container" style="float: right; margin-left: 1em; text-align: right;"><tbody>
<tr><td style="text-align: center;"><a href="http://payload52.cargocollective.com/1/7/236748/3340071/tumblr%20quote.jpg" imageanchor="1" style="clear: right; margin-bottom: 1em; margin-left: auto; margin-right: auto;"><img border="0" height="164" src="http://payload52.cargocollective.com/1/7/236748/3340071/tumblr%20quote.jpg" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;"><a href="http://cargocollective.com/ruthgraham/Dog-Eat-Dog">Dog-Eat-Dog by Ruth Graham</a></td></tr>
</tbody></table>
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There are important differences between
humans and other animals, and we should account for them when trying to model their respective behaviours. One difference is that humans can understand mathematical models,
while there is no known example of this in animals.</div>
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<span lang="EN-GB">In economics, <a href="http://people.bu.edu/rking/REmodels/lucascr.pdf">the Lucas critique</a> is a
useful piece of advice about modelling human behaviour. It alerts us to the
fact that if people are aware of the model we are using to predict their
behaviour, they can adjust their behaviour to exploit our naivety. Even if they
don’t know the exact model we are using, if we have not accounted for their
strategic behaviour, they can still take advantage of us.<o:p></o:p></span></div>
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<span lang="EN-GB">One paradox about the Lucas
critique goes as follows. Lets take the classic example of a model, called the
Philip’s curve, used by central bank managers to set inflation and try to
reduce unemployment. This model is subject to exploitation by rational firms
who can manipulate their employment patterns given that they know the inflation
strategy of the bankers. As a result, the Philip’s curve will fail to make a
correct prediction and is thus subject to the Lucas critique.<o:p></o:p></span></div>
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<span lang="EN-GB">This is a reasonable observation, but why are the firms assumed to be rational and the central
bank managers irrational? Surely, these highly qualified, trained economists
would have thought of this possibility and incorporated the reaction of the
firms into their model? This is all the more surprising when you consider that firms
have many other things to think about than inflation five years in to the
future. Apparently, on top of all their immediate concerns about their business
model, staffing problems etc. these firms have dedicated their time to finding
loopholes in the central bank’s thinking.<span style="mso-spacerun: yes;">
</span>Why should the bankers (apart from Lucas, of course) have missed this
fact, while the firms are able to work it out? <o:p></o:p></span></div>
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<span lang="EN-GB">Any Lucas-inspired model of these
bankers behaviour should not allow them to use the Philip’s curve in the first
place. The only logical conclusion of this line of reasoning is either that the
observations of the economists using Philip’s curves was mistaken or it was
some temporary insanity which is replaced by a steady state rationality in the
future. <span style="mso-spacerun: yes;"> </span></span></div>
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<span lang="EN-GB">When we build a mathematical model of human
behaviour, the Lucas critique should be taken seriously. Understood properly, it
says you should think a few steps ahead when making your model. Does your model
make sense? Lucas was pointing out that the Philip’s curve model has a
particular type of limitation. We should remember this limitation when we are
building models. The Lucas critique is <a href="http://mainlymacro.blogspot.co.uk/2012/08/the-lucas-critique-and-internal.html">one of many such limitations</a>. <o:p></o:p></span></div>
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<span lang="EN-GB">But the paradox tells us that the Lucas critque
should not be taken too seriously either. Taken to an extreme, the critique
says that the only thing economic models should be used for is studying the
outcome of rational interactions. If this were the case, then the paradoxical question
is why economics exists at all? The rationality assumption is that people are
able to work out the consequences of their actions and therefore we don’t need
an economist or anyone else presenting them with a model of what those
consequences might be. <o:p></o:p></span></div>
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This description is typical of paradoxes in mathematics where we want to say something about a model using the model itself to say it. Last month I wrote a blog post about <a href="http://collective-behavior.blogspot.se/2013/11/mathematics-beauty-warm-and-near.html">Bertrand Russell spending 20 years doing this to no avail in trying to establish the axioms of mathematics</a>. It just isn’t possible.</div>
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<span lang="EN-GB">I was prompted to write this after a <a href="http://mainlymacro.blogspot.se/2013/12/microfoundations-illusion-of-necessary.html?utm_source=feedburner&utm_medium=twitter&utm_campaign=Feed:+MainlyMacro+(mainly+macro)">blog post</a> by Simon Wren-Lewis that Richard Mann tweeted me. Although I find <a href="http://www.theguardian.com/commentisfree/2013/oct/28/mainstream-economics-denial-world-changed">scathing attacks on economics amusing</a>, I find it difficult to believe that economists or
anyone else takes the Lucas critique as far as appears to be claimed.<span style="mso-spacerun: yes;"> </span>This would be completely irrational. I also
doubt whether, <a href="http://webserver.tudor.lu/cms/lu2020/publishing.nsf/a375463375b95717c125703700349148/f24cd453e8d89216c12577ea00512649/$FILE/Alan%20Kirman_article%20complet.pdf">as is also claimed</a>, that we can really attribute
the economic crisis to models based on rationality.<span style="mso-spacerun: yes;">
</span>But it is certainly fun thinking about it.<o:p></o:p></span></div>
David Sumpterhttp://www.blogger.com/profile/09916867606281043665noreply@blogger.com0